جست‌وجوی استاد و پژوهشگر

• Clinical Social Work
• Adolescent High-Risk Behaviors
• Evidence-Based Practices Implementation
• +۳ مورد دیگر

Hanni Flaherty, Ph.D., serves as an Assistant Professor and Licensed Clinical Social Worker at Yeshiva University. With over a decade of clinical social work experience specializing in adolescent high-risk behaviors, she bridges practical clinical expertise with academic instruction in social work education. Her dual role as practitioner and educator informs her focus on evidence-based interventions and pedagogical innovation. Professor Flaherty's research centers on clinical social work practice implementation and the transition to online education, examining factors that facilitate adoption of evidence-based practices in youth mental health clinics. Her work explores technology integration in social work training, self-care mechanisms for students, and addressing disparities among vulnerable populations like sexual and gender minority youth. She investigates how simulated role-plays, virtual reality, and data analysis tools can enhance clinical training and student outcomes. Analysis of her 2023-2025 publications reveals dominant themes in educational technology adoption (R programming, VR simulations), evidence-based practice implementation, and specialized interventions for adolescent populations. Her scholarship consistently addresses the research-practice gap while adapting to digital learning environments, with particular attention to private practice development, substance use disparities, and secondary traumatic stress in student populations. No scientific awards were documented in the source materials. Her advisory activities remain unspecified, though her research on student self-efficacy and trauma exposure suggests active engagement with graduate trainees. No dedicated laboratories or research teams were referenced, but her work implies collaboration with mental health clinics serving youth populations and online education technology partners like Everspring.

Lingyu Wangمشاهده پروفایل

استاد مدعو

• Cloud Security
• Network Security
• Software Security
• +۳ مورد دیگر

Lingyu Wang is an Affiliate Professor at the Concordia Institute for Information Systems Engineering, Concordia University. He holds a Ph.D. in Information Technology from George Mason University (2006). His research focuses on cloud security, SDN/NFV security, security metrics, network security, software security, and privacy preservation. Dr. Wang has published extensively on topics including differential privacy systems, proactive security policy enforcement in containers, and cross-cluster security models for edge-core environments. His work also addresses challenges in securing industrial systems like IEC 61850 substations and 5G networks, leveraging techniques such as state auditing and event monitoring. His recent articles emphasize balancing security with performance efficiency, such as optimizing anomaly detection while preserving privacy and developing tools for real-time inconsistency detection in NFV environments. He has contributed to frameworks like ProSAS for proactive security auditing and VinciDecoder for automated forensic reporting in cloud environments. Dr. Wang’s research bridges theoretical cybersecurity principles with practical applications in cloud infrastructure, emphasizing resilience against zero-day attacks and supply chain vulnerabilities. His work frequently integrates machine learning and deep learning for enhanced security analysis and tool development.

• Computer Architecture
• Reliability Engineering
• Cloud Computing
• +۷ مورد دیگر

Professor Gizopoulos Dimitris is a faculty member at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on advanced topics in computer architecture, reliability engineering, and hardware security. With a strong emphasis on fault tolerance and computational integrity, his work addresses critical challenges in modern computing systems such as silent data corruptions, GPU reliability, and RISC-V cloud ecosystems. Key research interests include microarchitecture-level analysis, cross-layer system reliability assessment, and energy-efficient computing. His contributions span fault propagation modeling, hardware-software co-design for resilience, and innovative approaches to detecting silent errors in CPUs and GPUs. He actively participates in large-scale projects like NEUROPULS and Vitamin-V, advancing secure neuromorphic architectures and open-source cloud infrastructure. Recent publications highlight trends in silent data corruption quantification, GPU vulnerability analysis, and energy-efficient RISC-V designs. His work bridges theoretical models with practical implementations, emphasizing real-world validation through frameworks like gem5 and fault injection experiments. Despite no listed advisees or grants in current records, his research collaborations and project leadership position him at the forefront of next-generation computing reliability. Labs and teams associated with his work include the Vitamin-V virtual environment development team and the NEUROPULS consortium for secure neuromorphic accelerators. These initiatives reflect his commitment to advancing both theoretical and applied aspects of dependable computing systems.

Karakostas Vasileiosمشاهده پروفایل

استادیار

• Computer Architecture
• Cloud Computing
• RISC-V Processors
• +۵ مورد دیگر

Karakostas Vasileios is an Assistant Professor at the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens. His research focuses on computer architecture, cloud computing, and energy-efficient hardware systems. He specializes in areas such as RISC-V processors, virtual memory systems, and hardware security. Vasileios leads projects like NEUROPULS (neuromorphic secure accelerators) and Vitamin-V (RISC-V-based cloud infrastructure validation). His work emphasizes resilience analysis, performance optimization, and trustworthy development frameworks. Education and employment details are not explicitly provided in the source text, but his extensive publication record since 2011 demonstrates continuous academic engagement. Key research trends include: Memory systems optimization (e.g., TLB hierarchies, elastic translations) GPU and SoC fault tolerance analysis Cloud resource management (ACTiCLOUD, DAPHNE runtime) Open-source hardware validation (Vitamin-V project) Notable contributions include the Gem5-marvel simulator for heterogeneous architectures and BypassD for SSD access acceleration. His work bridges theoretical computer architecture with practical cloud and embedded system applications.

Shubhendu Mukherjeeمشاهده پروفایل

استاد مدعو

• Computer Architecture
• Fault Tolerant Systems
• Soft Errors
• +۵ مورد دیگر

Shubhendu Mukherjee is a Distinguished Engineer at Cavium Networks and Adjunct Professor at the Indian Institute of Technology Kanpur. He is a Fellow of IEEE and ACM, and recipient of the 2009 Maurice-Wilkes Award for outstanding contributions to computer architecture. His career spans leadership roles at Intel and Compaq, where he pioneered fault-tolerant microarchitectures and performance modeling innovations. Education: PhD (1998) and MS (1993) in Computer Science from University of Wisconsin-Madison; B.Tech (1991) in Computer Science and Engineering from IIT Kanpur. Research Interests Mukherjee specializes in computer architecture , soft error modeling , and fault-tolerant design . His work includes Redundant Multithreading (RMT), architectural vulnerability modeling, and on-chip interconnect optimization. Recent publications focus on cache soft error anomalies, quantized AVF analysis, and architectural core salvaging for hard error tolerance. Scientific Awards Maurice-Wilkes Award (2009) IEEE Fellow (2009) ACM Fellow (2011) IEEE Top Picks Awards (2003, 2004) Intel Divisional Recognition Awards (2002–2009) Professional Activities Mukherjee served as General Chair of ASPLOS 2004 , Program Chair of HPCA 2011 , and editorial board member for IEEE Micro, IEEE Computer Architecture Letters, and IEEE Transactions on Dependable and Secure Computing. He also led Intel's SPEARS group (2001–2010), driving architectural innovations in enterprise processors.

• Computer Engineering
• Hardware Security
• Artificial Intelligence
• +۳ مورد دیگر

Jaan Raik is a Tenured Full Professor and Head of the Centre for Dependable Computing Systems at Tallinn University of Technology (TalTech), Department of Computer Systems. His research focuses on hardware reliability, fault tolerance in embedded systems, and secure computing architectures. Key areas include fault-resilient deep neural network accelerators, approximation methods for DNNs, and vulnerability assessment in hardware-software systems. He leads the Centre for Dependable Computing Systems, which explores advanced reliability engineering techniques for modern computing systems. His work integrates formal verification, machine learning, and hardware design to address challenges in embedded systems, RISC-V processors, and edge AI chips. Notable contributions include frameworks like Saffira for DNN accelerator reliability assessment and innovative methods for assertion-based verification. Research interests span fault diagnosis, approximation computing, and security-aware architectures. He frequently publishes at top venues such as IEEE European Test Symposium and DDECS, with recent focus on resilient neural networks, cache leakage detection (CLD), and hardware Trojan mitigation. Collaborations include industry partnerships for practical deployment of fault-tolerant systems and academic initiatives to standardize reliability assessment methodologies. His work bridges theoretical computer engineering with applied solutions for real-world systems.

• Security of LLMs
• Log Analysis with LLMs
• Cybersecurity
• +۳ مورد دیگر

Valerii Gakh is a PhD student and Junior Research Fellow at Tallinn University of Technology's Department of Software Science (Faculty of Information Technologies). His research focuses on the security of large language models (LLMs) and their application in log analysis. He holds a Master's Degree from the same institution, where he defended his thesis on prompt injection detection solutions. Valerii is supervised by Hayretdin Bahşi and Risto Vaarandi in his doctoral studies exploring efficient security log template extraction using LLMs. Education: PhD Student (2024-), Tallinn University of Technology Master's Degree (2024), Tallinn University of Technology Research Interests: His work addresses critical challenges in AI security, including LLM vulnerability mitigation and leveraging LLMs for cybersecurity tasks like log analysis. Specific topics include prompt injection detection mechanisms and template extraction from security logs to enhance threat identification. Advising & Grants: Supervised by Professors Hayretdin Bahşi and Risto Vaarandi. No grants explicitly mentioned in the provided texts.

Liang Hongمشاهده پروفایل

استاد

• Wireless Communications
• Signal Processing
• Network Security
• +۲ مورد دیگر

Liang Hong is a Professor in the Department of Electrical and Computer Engineering at Tennessee State University. He earned his Ph.D. in Electrical Engineering from the University of Missouri-Columbia in 2002, following industry experience at Siemens Corporate Research. His research encompasses wireless communications, signal processing, network security, and embedded systems. Hong has led multiple federally funded projects including a $599,800 Office of Naval Research initiative on embedded system security and a $310,000 Air Force Research Laboratory program on spectrum communication. His extensive publications demonstrate consistent focus on cognitive radio networks, beamforming techniques, cybersecurity, and networked control systems. Recent work emphasizes AI applications for threat detection, cloud security, and adaptive resource management in wireless environments. Hong received the TSU Faculty Research Award (2005) and was nominated for Teacher of the Year (2010). He has chaired technical committees for IEEE conferences and guided award-winning student research.

Akramul Azimمشاهده پروفایل

دانشیار

• Real-Time Systems
• Embedded Software
• Safety-Critical Systems
• +۵ مورد دیگر

Dr. Akramul Azim is an Associate Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University, Faculty of Engineering and Applied Science. His research focuses on real-time systems, embedded software, safety-critical systems, IoT, software verification/validation, and applied machine learning. He leads the Real-Time Embedded Software Research (RTEMSOFT) Lab and has contributed to over 50 peer-reviewed publications. His work spans cybersecurity for automotive systems, edge computing optimization, and AI-driven software testing. Education: PhD (Electrical and Computer Engineering), University of Waterloo (2014) MSc (Computer Science and Engineering) (2009) BSc (Computer Science and Information Technology) (2006) Research Interests: Dr. Azim explores the intersection of real-time systems and machine learning, particularly in embedded environments. Key areas include: Autonomous vehicle safety Edge/IoT security Optimized task scheduling ML-enhanced software testing FPGA vulnerability mitigation Recent Research Trends: His publications (2023-2025) highlight advancements in LLM-based code optimization, lock contention mitigation in Java, energy-efficient vehicular networks, and safety-critical AI applications. Notable contributions include frameworks for situation-aware adaptation in ITS and reinforcement learning for edge task scheduling. Labs/Teams: Directs the RTEMSOFT Lab, collaborating on projects like AD-CGAN for anomaly detection and ESOps agile pipeline development.

• Network Security
• Cybersecurity
• Cloud Computing Security
• +۴ مورد دیگر

Martine Bellaïche is a Full Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. With a B.Sc., M.Sc., and Ph.D. from Montreal, she has established herself as a leading researcher in network security and cybersecurity. She is affiliated with the Mobile Computing and Networking Research Laboratory (LARIM), where she contributes to cutting-edge research in communications systems, networks, and algorithms. Dr. Bellaïche's research spans multiple critical areas of modern cybersecurity, with particular focus on network security, prevention and detection of attacks, performance evaluation of defense systems, and defense against Denial of Service (DDoS) attacks. Her work extends to specialized domains including sensor network security, vehicular network security, cloud computing security, and Internet of Things security. Her research approach often combines theoretical foundations with practical applications, addressing real-world security challenges across various technological domains. Analysis of her recent publications reveals a strong trend toward AI-driven security solutions, particularly using deep learning and federated learning approaches for intrusion detection in IoT environments. Her work increasingly addresses emerging security challenges in blockchain technology, metaverse applications, and industrial IoT systems, demonstrating adaptability to evolving technological landscapes while maintaining focus on fundamental security principles. Supervised 5 PhD students to completion, including Alfalqi (2022), Alghamdi (2022), Abusitta (2018), Halabi (2018), and Benbrahim (2016) Mentored 6 Master's students, with research spanning DDoS detection, VANET security, and graph coloring algorithms Active participant in multiple research grants, including Discovery Grants from Polytechnique Montréal Dr. Bellaïche teaches several foundational computer science courses including procedural programming, object-oriented programming, microcomputer architecture, and data structures and algorithms, bridging theoretical knowledge with practical security applications in her teaching.

Gabriela Nicolescuمشاهده پروفایل

استاد

• Cybersecurity for Avionics
• Security by Design for Cyber-Physical Systems
• Advanced Programming Models for Avionic Multi and Many-Core Systems
• +۱۱ مورد دیگر

Gabriela Nicolescu is a Professor at Polytechnique Montréal , affiliated with the Department of Computer Engineering and Software Engineering and the LAMA-WeST (Web, Semantics and Text) research group. Her work focuses on design methodologies , programming , and security for advanced systems integrating 3D SoCs , optical networks , and heterogeneous technologies . Education: B.Sc. and M.Sc., Politehnica Bucharest Ph.D., Institut National Polytechnique de Grenoble (2002), awarded Best Thesis in Microelectronics Research Interests include cybersecurity for avionics , security by design for cyber-physical systems , advanced programming models for multi-core systems , and modeling/simulation of heterogeneous systems . She has contributed to fields like optical networks on chip , real-time embedded systems , and edge computing security . Recent Publications highlight her leadership in all-optical neural networks , formal verification , and security for avionic systems . Her work spans machine learning-driven intrusion detection , photonic integrated circuits , and ontology-based cybersecurity frameworks . Scientific Awards: Best Thesis in Microelectronics, Institut National Polytechnique de Grenoble (2002) Student Supervision encompasses doctoral and master’s theses in areas such as multi-core RTOS , security in autonomous systems , AI-based penetration testing , and performance optimization in avionics . Current advisees include Felipe Magalhaes , Julien Carayol , and Kacem Khaled , while completed supervision includes A. S. Shahnejat Bushehri and Rami Zrelli . She is actively involved in collaborative research projects addressing national cybersecurity priorities and safer aircraft design , as highlighted in media outlets like The Globe and Mail and Science-Presse .

Tom Melhamمشاهده پروفایل

استاد

• Formal Verification
• Hardware Verification
• Theorem Proving
• +۲ مورد دیگر

Tom Melham is Professor of Computer Science at the University of Oxford, Tutorial Fellow at Balliol College, and Fellow of the Royal Society of Edinburgh. His research develops formal methods for hardware and software verification, with recent focus on security applications and neural network verification. Research interests include automated theorem proving, symbolic trajectory evaluation, hardware/software co-verification, and security assurance methods. Recent work applies formal verification to processor security, vulnerability management, and deep learning systems. Publications demonstrate foundational contributions to hardware verification methodologies, with increasing focus on security engineering and machine learning verification in recent years. Research integrates theoretical advances with practical industrial applications. Melham directs projects on processor security verification, automated exploit generation, and hybrid approaches to memory safety. He teaches computer science and law courses while advising graduate students in formal methods research.

Robert Lagerströmمشاهده پروفایل

استاد

• Cyber Security
• Information Systems
• Threat Modeling
• +۶ مورد دیگر

Robert Lagerström is a Professor at KTH Royal Institute of Technology specializing in Industrial Information Systems. His research focuses on developing automated cyber security frameworks and threat modeling methodologies for large-scale IT environments. Key areas include vulnerability analysis of IoT, automotive systems, and critical infrastructure, with a particular emphasis on probabilistic modeling and simulation languages like vehicleLang and powerLang. He collaborates extensively with industry partners across automotive, banking, energy, and cloud sectors to validate practical security solutions. His work emphasizes model-based security analysis that avoids disrupting live systems, enabling safe testing of cyber defenses. Notable contributions include the securiCAD tool for enterprise cyber security management and the PatrIoT framework for agile threat research in IoT ecosystems. Lagerström's research integrates enterprise architecture modeling with security behavior analysis, addressing challenges in digitalization and agile development environments. He has pioneered methods for quantifying attack resilience through probabilistic threat simulations and has published widely on topics such as LPWAN security, SCADA system vulnerabilities, and ethical considerations in offensive cyber training. His work bridges theoretical cyber security concepts with real-world implementation challenges in both traditional IT and emerging technologies like blockchain and microservices architectures.

• Cybersecurity
• Cybercrime Analysis
• Digital Forensics
• +۳ مورد دیگر

Nigel Phair is a Professor in the Department of Software Systems & Cybersecurity at Monash University, specializing in cybersecurity, cybercrime analysis, and digital forensics. His research focuses on global cybersecurity trends, corporate cybersecurity practices, and the intersections of law enforcement with digital platforms. Phair’s work frequently addresses critical issues such as cybercrime indices, boardroom cybersecurity competency, and the societal impact of digital technologies. He has contributed to national cybersecurity strategy discussions in Australia and explored challenges in law enforcement’s adaptation to digital crime landscapes. His publications highlight innovative methods like Automated Social Media Intelligence Analysis (ASMIA) for detecting illicit activities online and emphasize the disconnect between corporate cybersecurity claims and actual practices. He has also analyzed encryption’s role in balancing national security and privacy rights. While no awards or grants are explicitly listed, his extensive output reflects a commitment to advancing cybersecurity policy, education, and technical solutions. His research extends to global cybersecurity comparisons, digital financial service vulnerabilities, and the evolving threat landscapes in cyberspace.

Yang Liuمشاهده پروفایل

مدرس ارشد

• Data Security
• Privacy-Preserving Computing
• Federated Learning
• +۳ مورد دیگر

Dr. Yang Liu is a Senior Lecturer in the Department of Computer Science at Swansea University's Faculty of Science and Engineering. He holds a D.Phil. in Computer Science from the University of Oxford and specializes in data security, privacy-preserving computing, and blockchain technologies. Research Focus: Dr. Liu's work centers on secure computation frameworks with specific expertise in: Federated learning systems optimization Privacy-preserving smart contract design Blockchain security and regulation Cryptographic techniques for data protection Secure machine learning applications Recent publications demonstrate methodological innovations in adaptive federated learning algorithms, regulatable blockchain architectures, privacy-enhanced recommendation systems, and security vulnerability analysis in Ethereum networks. His research bridges theoretical cryptography with practical applications in cloud/edge computing environments.